More questions about multiple passions: Who has them, how many do people have, and the impact of being polyamorously passionate on well-being
Bibliographic record
Abstract
People are often passionate toward multiple activities in their lives. However, more has been learned about passion toward any single activity than about passion toward multiple activities. Relying on the dualistic model of passion (Vallerand 2015), this research addressed the antecedents and consequences of polyamorous passion. In three pre-registered studies (total N = 1,322) and one mini meta-analysis, we found that (a) people tend to report being passionate for between 2 and 4 activities; (b) harmonious passion becomes a less potent predictor of well-being as it is directed toward less-favored activities; (c) harmonious passion does not contribute to the prediction of well-being beyond a second-favorite activity; and (d) openness to experience is a personality trait that is positively associated with the number of passionate activities that people have in their lives. These results contribute to our understanding of who has multiple passions, how many passionate activities people tend to have, and the relationship between polyamorous passion and well-being.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".